A Parallel Hybrid Heuristic for the TSP
Proceedings of the EvoWorkshops on Applications of Evolutionary Computing
Vehicle Routing and Time Deadlines Using Genetic and Local Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
Multiple Vehicle Routing with Time and Capacity Constraints Using Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
EuroGP '98 Proceedings of the First European Workshop on Genetic Programming
Models, relaxations and exact approaches for the capacitated vehicle routing problem
Discrete Applied Mathematics
A comprehensive survey of fitness approximation in evolutionary computation
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Multi-Objective Genetic Algorithms for Vehicle Routing Problem with Time Windows
Applied Intelligence
Two memetic algorithms for heterogeneous fleet vehicle routing problems
Engineering Applications of Artificial Intelligence
The multi-objective uncapacitated facility location problem for green logistics
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A hybrid heuristic for the traveling salesman problem
IEEE Transactions on Evolutionary Computation
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This paper makes the assertion that vehicle routing rearch has produced increasingly more powerful problem solvers, but has not increased the realism or compexity of typical problem instances. This paper argues that the time has come of use realistic street network data to increase the relevence and challenge of our work. A particular benefit of real world street data is the ability to support vehicle emissions modeling. Thus allowing emissions to be used as an optimisation criterion. Two on-line demonstrations are presented which demonstrate the use of GIS data obtained from Open Street Map and Google Maps. The demonstrations prove the concept that Evolutionary Algorithms may be used to solve problem instances that are based upon GIS derrived data.